Michael R. Zhang

Artificial Intelligence · 2021

A researcher in the Science corpus: 3 papers; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 94 citations into it
• Reinforcement Learning — 91 citations into it
• Management Science and Operations Research — 34 citations into it
• Statistics and Probability — 18 citations into it

Whom Michael R. Zhang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Diederik P. Kingma
3. Ofir Nachum
4. Geoffrey E. Hinton
5. Sergey Levine
6. Yoshua Bengio
7. Doina Precup
8. Alex Krizhevsky
9. Jimmy Ba
10. Josiah P. Hanna

Who trusts Michael R. Zhang overall

1. Michael Janner
2. Justin Fu
3. Qiyang Li

Papers from Michael R. Zhang's perspective

Ordered by how strongly the researchers Michael R. Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Benchmarks for Deep Off-Policy Evaluation (2021) — 117 citations
• Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization (2021) — 53 citations
• Learning Domain Invariant Representations in Goal-conditioned Block MDPs (2021) — 19 citations